Project Summary Limited evidence suggests that periodontal treatment may improve cardiovascular and diabetes outcomes in some groups. Despite these findings, critical gaps remain in our understanding of the relationship between periodontal disease and these medical conditions. The proposed study will utilize a relational database combining 12 years of medical, pharmacy, laboratory, dental, and insurance claims data from a large, community-based, integrated health system to explore whether treatment of periodontal disease can improve select medical outcomes and reduce medical costs when controlling for confounders not previously addressed in studies utilizing observational data. By leveraging longitudinal (repeated measures) data, we will have access to more relevant measures over longer follow-up times relative to previous reports. In addition, we will use additional statistical approaches?compared side by side with traditional epidemiological results?that, by design, aim to control for unmeasured confounders (e.g., attitudes, personality, unobserved health habits) that remain relatively stable over time or aim to leverage quasi-experimental properties in the data (i.e., instrumental variables) to approximate causal effects as if periodontal treatment were randomly assigned. We anticipate that effect estimates may be attenuated (or even eliminated) relative to previously reported results when confounding is better controlled for by using richer data and more sophisticated analytic methods afforded by those richer data. If previous findings hold up to our more robust probing, we believe the added confidence in those results will bring substantial value to informing clinical priority setting.